オンラインまたはオンサイトのインストラクター主導のライブApache Kafkaトレーニングコースでは、インタラクティブなディスカッションと実践的な練習を通じて、Kafka メッセージ・ブローカーを設定および操作する方法を示します。
Kafkaトレーニングは、「オンラインライブトレーニング」または「オンサイトライブトレーニング」として利用できます。オンラインライブトレーニング（別名「リモートライブトレーニング」） は、インタラクティブなリモートデスクトップを使用して実行されます。現地でのライブトレーニングは、日本のお客様のオフィスまたは日本のNobleProg提携の企業トレーニングセンターでにて現地での実施が可能です。
Kafkaトレーニングコースでは、Kafkaと他のビッグ・データ・システムとの統合、およびストリーミング・アプリケーション用のリアルタイム・データ・パイプラインの設定方法について説明します。
NobleProg - 現地のトレーニングプロバイダー
お客様の声
講師はトピックを説明するのに彼の時間を与えます、そして我々はkafka corriendpを持っているために必要なソフトウェアのインストールの問題で多くに詳しく見ます
Juan Manuel Del Alto - Hewlett Packard Centro de Servicios Globales S de RL
コース: Distributed Messaging with Apache Kafka
Machine Translated
有益で、正確なレベルの詳細を私は信じていた。
Asif Akhtar
コース: Distributed Messaging with Apache Kafka
Machine Translated
私は本当に簡単に従うことから恩恵を受けました。
Zach Henke
コース: Distributed Messaging with Apache Kafka
Machine Translated
練習問題、特にうまくいかなかったとき（明らかに私のせいだが、失敗発見は仕事の一部です）。
Peter Hendriks
コース: Distributed Messaging with Apache Kafka
Machine Translated
私は主にトレーナーの知識を気に入っていました。
Christian Langer
コース: Distributed Messaging with Apache Kafka
Machine Translated
私は真に詳細な説明、よく準備された文書を本当に好きだった。
Allen Jeong
コース: Distributed Messaging with Apache Kafka
Machine Translated
私は実用的なアドバイス（カフカの設定と管理）の恩恵を受けました。
OLAmobile
コース: Distributed Messaging with Apache Kafka
Machine Translated
私は実践的な例から恩恵を受けていました。
Rumos
コース: Distributed Messaging with Apache Kafka
Machine Translated
トレーナーは本当にカフカをとてもよく知っていて、この問題で多くの生産経験を持っています。
Matej Puntra
コース: Distributed Messaging with Apache Kafka
Machine Translated
トレーニングは、チームが望む方向に向けられました。トレーナーは、スケーラビリティ、パフォーマンス、開発および展開の標準などの概念を扱う豊富な経験と、コード、設計、アーキテクチャ、ベストプラクティスなどに関するさまざまなレベルからのクエリに対応するためのトレーニングに非常に迅速です。
Sarita Velagapudi - Welcome Real-time (ASPAC) Pte Ltd
コース: Distributed Messaging with Apache Kafka
Machine Translated
概念、それが提示する方法、非常にコミュニケーション、非常に有用な、広い知識。
Sreenivasulu Narasingu - Welcome Real-time (ASPAC) Pte Ltd
コース: Distributed Messaging with Apache Kafka
Machine Translated
私は主に話題の量を楽しんだ。
Ipreo
コース: Distributed Messaging with Apache Kafka
Machine Translated
トレーナーと簡単に話せます。
VSC Technologies
コース: Distributed Messaging with Apache Kafka
Machine Translated
コーチのアプローチ、知識を伝達する方法。
Ośrodek Przetwarzania Informacji-Państwowy Instytut Badawczy
コース: Distributed Messaging with Apache Kafka
Machine Translated
実施方法、実践的演習
darek lesiak - Ośrodek Przetwarzania Informacji-Państwowy Instytut Badawczy
コース: Distributed Messaging with Apache Kafka
Machine Translated
トピック
Ośrodek Przetwarzania Informacji-Państwowy Instytut Badawczy
コース: Distributed Messaging with Apache Kafka
Machine Translated
インタラクティブ性、トレーナーとの接触、客観性
Ośrodek Przetwarzania Informacji-Pańswowy Instytut Badawczy
コース: Distributed Messaging with Apache Kafka
Machine Translated
リスナーとの良好な接触、トレーナーのかなりの知識。
Ośrodek Przetwarzania Informacji-Pańswowy Instytut Badawczy
コース: Distributed Messaging with Apache Kafka
Machine Translated
興味深い演習の例
Ośrodek Przetwarzania Informacji-Pańswowy Instytut Badawczy
コース: Distributed Messaging with Apache Kafka
Machine Translated
面白い演習で、Apache Kafkaのアーキテクチャーと操作をダイアグラムに示します。
Damian Niesteruk - Ośrodek Przetwarzania Informacji-Pańswowy Instytut Badawczy
コース: Distributed Messaging with Apache Kafka
Machine Translated
知識は講師にとって間違いない利点です。
Ośrodek Przetwarzania Informacji-Pańswowy Instytut Badawczy
コース: Distributed Messaging with Apache Kafka
Machine Translated
議論されたトピックのキーポイントのリコール/レビュー。
Paolo Angelo Gaton - SMS Global Technologies Inc.
コース: Building Stream Processing Applications with Kafka Streams
Machine Translated
-
Roxane Santiago - SMS Global Technologies Inc.
コース: Building Stream Processing Applications with Kafka Streams
Machine Translated
ラボでの演習。翌日から初日から理論を適用する。
Dell
コース: A Practical Introduction to Stream Processing
Machine Translated
すべてのトピックが前のトピックの拡張であったこと。トレーナーはとても親切で親切でした。
Pavel Ignatov - Пейсейф България ЕООД
コース: Microservices with Spring Cloud and Kafka
Machine Translated
トレーナーは非常に広範な知識と経験を持っていたため、トレーニングの分野で尋ねられたすべての質問に答えることができました。あなたがしなければならなかったのは彼らに尋ねるだけでした。
Powszechny Zakład Ubezpieczeń Spółka Akcyjna
コース: Kafka for Administrators
Machine Translated
理論対運動比、理論中にリスナーに興味を持たせる優れた能力
Powszechny Zakład Ubezpieczeń Spółka Akcyjna
コース: Kafka for Administrators
Machine Translated
すべての。
Jean-Michel Bidon
コース: Kafka for Administrators
Machine Translated
Apache Kafkaコース概要
コース名
期間
概要
コース名
期間
概要
14 時間
概要
This course is for enterprise architects, developers, system administrators and anyone who wants to understand and use a high-throughput distributed messaging system. If you have more specific requirements (e.g. only system administration side), this course can be tailored to better suit your needs.
14 時間
概要
Apache Samza is an open-source near-realtime, asynchronous computational framework for stream processing. It uses Apache Kafka for messaging, and Apache Hadoop YARN for fault tolerance, processor isolation, security, and resource management.
This instructor-led, live training introduces the principles behind messaging systems and distributed stream processing, while walking participants through the creation of a sample Samza-based project and job execution.
By the end of this training, participants will be able to:
- Use Samza to simplify the code needed to produce and consume messages.
- Decouple the handling of messages from an application.
- Use Samza to implement near-realtime asynchronous computation.
- Use stream processing to provide a higher level of abstraction over messaging systems.
Audience
- Developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
This instructor-led, live training introduces the principles behind messaging systems and distributed stream processing, while walking participants through the creation of a sample Samza-based project and job execution.
By the end of this training, participants will be able to:
- Use Samza to simplify the code needed to produce and consume messages.
- Decouple the handling of messages from an application.
- Use Samza to implement near-realtime asynchronous computation.
- Use stream processing to provide a higher level of abstraction over messaging systems.
Audience
- Developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
7 時間
概要
Kafka Streams is a client-side library for building applications and microservices whose data is passed to and from a Kafka messaging system. Traditionally, Apache Kafka has relied on Apache Spark or Apache Storm to process data between message producers and consumers. By calling the Kafka Streams API from within an application, data can be processed directly within Kafka, bypassing the need for sending the data to a separate cluster for processing.
In this instructor-led, live training, participants will learn how to integrate Kafka Streams into a set of sample Java applications that pass data to and from Apache Kafka for stream processing.
By the end of this training, participants will be able to:
- Understand Kafka Streams features and advantages over other stream processing frameworks
- Process stream data directly within a Kafka cluster
- Write a Java or Scala application or microservice that integrates with Kafka and Kafka Streams
- Write concise code that transforms input Kafka topics into output Kafka topics
- Build, package and deploy the application
Audience
- Developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Notes
- To request a customized training for this course, please contact us to arrange
In this instructor-led, live training, participants will learn how to integrate Kafka Streams into a set of sample Java applications that pass data to and from Apache Kafka for stream processing.
By the end of this training, participants will be able to:
- Understand Kafka Streams features and advantages over other stream processing frameworks
- Process stream data directly within a Kafka cluster
- Write a Java or Scala application or microservice that integrates with Kafka and Kafka Streams
- Write concise code that transforms input Kafka topics into output Kafka topics
- Build, package and deploy the application
Audience
- Developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Notes
- To request a customized training for this course, please contact us to arrange
21 時間
概要
In this instructor-led, live training in 日本 (onsite or remote), participants will learn how to set up and integrate different Stream Processing frameworks with existing big data storage systems and related software applications and microservices.
By the end of this training, participants will be able to:
- Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming.
- Understand and select the most appropriate framework for the job.
- Process of data continuously, concurrently, and in a record-by-record fashion.
- Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
- Integrate the most appropriate stream processing library with enterprise applications and microservices.
By the end of this training, participants will be able to:
- Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming.
- Understand and select the most appropriate framework for the job.
- Process of data continuously, concurrently, and in a record-by-record fashion.
- Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
- Integrate the most appropriate stream processing library with enterprise applications and microservices.
14 時間
概要
This instructor-led, live training (online or onsite) is aimed at engineers who wish to use Confluent (a distribution of Kafka) to build and manage a real-time data processing platform for their applications.
By the end of this training, participants will be able to:
- Install and configure Confluent Platform.
- Use Confluent's management tools and services to run Kafka more easily.
- Store and process incoming stream data.
- Optimize and manage Kafka clusters.
- Secure data streams.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- This course is based on the open source version of Confluent: Confluent Open Source.
- To request a customized training for this course, please contact us to arrange.
By the end of this training, participants will be able to:
- Install and configure Confluent Platform.
- Use Confluent's management tools and services to run Kafka more easily.
- Store and process incoming stream data.
- Optimize and manage Kafka clusters.
- Secure data streams.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- This course is based on the open source version of Confluent: Confluent Open Source.
- To request a customized training for this course, please contact us to arrange.
7 時間
概要
Apache Kafka is a distributed streaming platform. It is de facto a standard for building data pipelines and it solves a lot of different use-cases around data processing: it can be used as a message queue, distributed log, stream processor, etc.
We'll start with some theory behind data pipelines in general, then continue with fundamental concepts behind Kafka. We'll also discover important components like Kafka Streams and Kafka Connect.
We'll start with some theory behind data pipelines in general, then continue with fundamental concepts behind Kafka. We'll also discover important components like Kafka Streams and Kafka Connect.
21 時間
概要
This instructor-led, live training in 日本 (online or onsite) is aimed at developers who wish to transform traditional architecture into a highly concurrent microservices-based architecture using Spring Cloud, Kafka, Docker, Kubernetes and Redis.
By the end of this training, participants will be able to:
- Set up the necessary development environment for building microservices.
- Design and implement a highly concurrent microservices ecosystem using Spring Cloud, Kafka, Redis, Docker and Kubernetes.
- Transform monolithic and SOA services to microservice based architecture.
- Adopt a DevOps approach to developing, testing and releasing software.
- Ensure high concurrency among microservices in production.
- Monitor microservices and implement recovery strategies.
- Carry out performance tuning.
- Learn about future trends in microservices architecture.
By the end of this training, participants will be able to:
- Set up the necessary development environment for building microservices.
- Design and implement a highly concurrent microservices ecosystem using Spring Cloud, Kafka, Redis, Docker and Kubernetes.
- Transform monolithic and SOA services to microservice based architecture.
- Adopt a DevOps approach to developing, testing and releasing software.
- Ensure high concurrency among microservices in production.
- Monitor microservices and implement recovery strategies.
- Carry out performance tuning.
- Learn about future trends in microservices architecture.
7 時間
概要
This instructor-led, live training in 日本 (online or onsite) is aimed at developers who wish to integrate Apache Kafka with existing databases and applications for processing, analysis, etc.
By the end of this training, participants will be able to:
- Use Kafka Connect to ingest large amounts of data from a database into Kafka topics.
- Ingest log data generated by an application servers into Kafka topics.
- Make any collected data available for stream processing.
- Export data from Kafka topics into secondary systems for storage and analysis.
By the end of this training, participants will be able to:
- Use Kafka Connect to ingest large amounts of data from a database into Kafka topics.
- Ingest log data generated by an application servers into Kafka topics.
- Make any collected data available for stream processing.
- Export data from Kafka topics into secondary systems for storage and analysis.
7 時間
概要
This instructor-led, live training in 日本 (online or onsite) is aimed at developers who wish to implement Apache Kafka stream processing without writing code.
By the end of this training, participants will be able to:
- Install and configure Confluent KSQL.
- Set up a stream processing pipeline using only SQL commands (no Java or Python coding).
- Carry out data filtering, transformations, aggregations, joins, windowing, and sessionization entirely in SQL.
- Design and deploy interactive, continuous queries for streaming ETL and real-time analytics.
By the end of this training, participants will be able to:
- Install and configure Confluent KSQL.
- Set up a stream processing pipeline using only SQL commands (no Java or Python coding).
- Carry out data filtering, transformations, aggregations, joins, windowing, and sessionization entirely in SQL.
- Design and deploy interactive, continuous queries for streaming ETL and real-time analytics.
21 時間
概要
This instructor-led, live training in 日本 (online or onsite) is aimed at sysadmins who wish to set up, deploy, manage and optimize an enterprise-grade Kafka cluster.
By the end of this training, participants will be able to:
- Set up and administer a Kafka Cluster.
- Evaluate the benefits and disadvantages of deploying Kafka on-premise vs in the cloud.
- Deploy and monitor Kafka in using various on-premise and cloud environment tools.
By the end of this training, participants will be able to:
- Set up and administer a Kafka Cluster.
- Evaluate the benefits and disadvantages of deploying Kafka on-premise vs in the cloud.
- Deploy and monitor Kafka in using various on-premise and cloud environment tools.
7 時間
概要
This instructor-led, live training in 日本 (online or onsite) is aimed at software testers who wish to implement network security measures into an Apache Kafka application.
By the end of this training, participants will be able to:
- Deploy Apache Kafka onto a cloud based server.
- Implement SSL encryption to prevent attacks.
- Add ACL authentication to track and control user access.
- Ensure credible clients have access to Kafka clusters with SSL and SASL authentication.
By the end of this training, participants will be able to:
- Deploy Apache Kafka onto a cloud based server.
- Implement SSL encryption to prevent attacks.
- Add ACL authentication to track and control user access.
- Ensure credible clients have access to Kafka clusters with SSL and SASL authentication.
14 時間
概要
This instructor-led, live training in 日本 (online or onsite) is aimed at data scientists who wish to use the SMACK stack to build data processing platforms for big data solutions.
By the end of this training, participants will be able to:
- Implement a data pipeline architecture for processing big data.
- Develop a cluster infrastructure with Apache Mesos and Docker.
- Analyze data with Spark and Scala.
- Manage unstructured data with Apache Cassandra.
By the end of this training, participants will be able to:
- Implement a data pipeline architecture for processing big data.
- Develop a cluster infrastructure with Apache Mesos and Docker.
- Analyze data with Spark and Scala.
- Manage unstructured data with Apache Cassandra.
7 時間
概要
This instructor-led, live training in 日本 (online or onsite) is aimed at data engineers, data scientists, and programmers who wish to use Apache Kafka features in data streaming with Python.
By the end of this training, participants will be able to use Apache Kafka to monitor and manage conditions in continuous data streams using Python programming.
By the end of this training, participants will be able to use Apache Kafka to monitor and manage conditions in continuous data streams using Python programming.
7 時間
概要
This instructor-led, live training in 日本 (online or onsite) is aimed at data engineers, data scientists, and programmers who wish to use Spark Streaming features in processing and analyzing real-time data.
By the end of this training, participants will be able to use Spark Streaming to process live data streams for use in databases, filesystems, and live dashboards.
By the end of this training, participants will be able to use Spark Streaming to process live data streams for use in databases, filesystems, and live dashboards.
今後のApache Kafkaコース
05-10-2021 10:00
21 時間
12-10-2021 10:00
21 時間
03-11-2021 10:00
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